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A simple, descriptive and interpretable model, based on a quantitative structure-retention relationship (QSRR), was developed using the genetic algo- rithm-multiple linear regression (GA-MLR) approach for the prediction of the retention indices (RI) of essential oil components. By molecular modeling, three significant descriptors related to the RI values of the essential oils were identified. A data set was selected consisting of the retention indices for 32 essential oil molecules with a range of more than 931 compounds. Then, a suit- able set of the molecular descriptors was calculated and the important descrip- tors were selected with the aid of the genetic algorithm and multiple regression method. A model with a low prediction error and a good correlation coefficient was obtained. This model was used for the prediction of the RI values of some essential oil components which were not used in the modeling procedure.

A quantitative structure-retention relationship for the prediction of retention indices of the essential oils of Ammoides atlantica